Many projects suffer from structural issues like tight coupling, code duplication, and scalability challenges that create business costs.
Poor code quality leads to significant business costs, including slower development speed, higher defect rates, and wasted developer time.
Clean architecture provides a structural foundation with four concentric layers governed by the dependency inversion principle.
The principles of clean architecture directly address problems like tight coupling and testing complexity through modular layers and framework independence.
The Model-View-ViewModel (MVVM) pattern complements clean architecture by providing specific guidance for the presentation layer, decoupling the UI from business logic.
Together, clean architecture and MVVM create a complete architectural approach with clear boundaries, enhanced testability, and a scalable structure.
A simple to-do application serves as a learning tool to demonstrate every architectural pattern, including dependency flow and data flow across layers.
The project's folder structure mirrors the clean architecture layers, and a dependency injection container manages dependencies to enable inversion of control.
The view component is kept simple and focused on rendering the UI and forwarding user events to the view model, with no business logic or state management.
The view model, implemented as a custom React hook, manages presentation logic and state, acting as a bridge between the view and the use cases.
Use cases orchestrate complex business workflows, while repositories handle data access by implementing interfaces defined in the domain layer.
The combined architecture solves the initial problems by creating a maintainable, testable, and framework-independent application with clear separation of concerns.
These patterns are ideal for complex, long-lived applications with multiple teams but are overkill for simple CRUD apps, prototypes, or short-term projects.
Start simple and evolve your architecture based on business needs, focusing on solving real problems like tight coupling and testability.
Jobs that call for the skills explored in this talk.